Abstract
During odour recognition, excitatory and inhibitory groups of neurons in the second stage of the locust olfactory system, the anten- nal lobe (AL), fire alternately. There is little spread in the firing times within each group. Locust anatomy and physiology help to pin down all parameters apart from the weights in a coarse spiking neuron model of the AL. The time period and phase of the group oscillations do however constrain the weights; this paper investigates how.
I generalise the spiking neuron locking theorem [3] to derive conditions that allow stable synchronous firing within multiple groups. I then apply the general result to the AL model. The most important result is that for a general form of postsynaptic potential (PSP) function the excitatory and inhibitory neuronal populations cannot fire alternately at certain time periods and phases, regardless of the size of the weights between and within groups.
I generalise the spiking neuron locking theorem [3] to derive conditions that allow stable synchronous firing within multiple groups. I then apply the general result to the AL model. The most important result is that for a general form of postsynaptic potential (PSP) function the excitatory and inhibitory neuronal populations cannot fire alternately at certain time periods and phases, regardless of the size of the weights between and within groups.
| Original language | English |
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| Title of host publication | Emergent Neural Computational Architectures Based on Neuroscience |
| Subtitle of host publication | Towards Neuroscience-Inspired Computing |
| Publisher | Springer |
| Pages | 270-284 |
| Number of pages | 15 |
| ISBN (Electronic) | 978-3-540-44597-5 |
| ISBN (Print) | 978-3-540-42363-8 |
| DOIs | |
| Publication status | Published - Jul 2001 |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Publisher | Springer Berlin Heidelberg |
| Volume | 2036 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |